Overview

We started to use Azure Service Bus (ASB) as an enterprise messaging solution 3 years ago. It is being used to publish and consume data between many applications in the organization. Since the data flow is complex, and one application’s data is usually needed in multi applications the “publisher” ---> ”multiple subscribers” model was a great fit. The ASB usage in the organization is dozens of millions of messages per day, while IRIS platform is having around 2-3 million messages/day.

Some time ago I introduced a new driver for Django for IRIS. Now, let's see how to use Django with IRIS in practice.

What is Web Scraping:

In simple terms, Web scraping, web harvesting, or web data extraction is an automated process of collecting large data(unstructured) from websites. The user can extract all the data on particular sites or the specific data as per the requirement. The data collected can be stored in a structured format for further analysis.

Steps involved in web scraping:

1. Find the URL of the webpage that you want to scrape
2. Select the particular elements by inspecting
3. Write the code to get the content of the selected elements
4. Store the data in the required format

It’s that simple !

Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python. This article details how to create new SQL Stored Procedures in InterSystems IRIS Database using Embedded Python.

My major interest is  Working with Globals in Embedded Python.
So I checked the available official documentation.

#1 Introduction to Globals
an attempt of a generic description of what a global is. Pointing to

#2 A Closer Look at ObjectScript
But where is Embedded Python ?
Way down you see

#3 Embedded Python

3.1 Embedded Python Overview
3.1.1 Work with Globals
Great if you have never seen a Global before
Otherwise a shocking primitive example
3.2 Using Embedded Python
Last hope: >>> but there is just NOTHING visible.
This is more than just disappointing! Even IRIS Native API for Python is more detailed.

Hi Community,

This post is a introduction of my open exchange iris-climate-change application.

iris-climate-change  web application Imports  The Food and Agriculture Organization (FAO) Climate Change dataset by using LOAD DATA (SQL) functionality and analyze and visualize data with the help of Python Flask Web Framework, Pandas Python data analysis Library, Plotly Open Source Graphing Library for Python and Plotly JavaScript Open Source Graphing Library.

Date and Time is an important factors in our life. Because all applications are engaging based on Date/Time. But our world is split into multiple time zones. if our product is launched in the world, to maintain the history of events we are definitely required to convert all times to our local time or UTC ( Coordinated Universal Time ). As I know, many known programming languages of C#, JavaScript, Java, etc., provided the library to convert the date and time. i.e with a time zone name we can be able to convert without knowing the UTC offset.

TZ database doesn't exist in InterSystems products.

Hi developers! In this article I’m going to explore the use of Iris Python Native API in a specific problem: large strings to store.

Why Python Native API?

Python Native API for Intersystems IRIS offers an useful way to persist data that you can’t have control over the schema or if the schema changes frequently. Combining the Native API with the IRIS Globals, you can easily use Iris Database as an Document Store. You can also see more details of globals use in this video in online learning (https://learning.intersystems.com/course/view.php?name=Native%20API%20for%20Python)

Hi Community,

In this article I will explain how to display management portal dashboard by using Python Flask web and Boostrap framework with the help of embedded python

In the first part, I've shown how to start a new project on Django, as well as define new models and add already existing models.

This time, I'll introduce an admin panel, available out of the box and how it can be useful.

Important note: do not expect that if you try to repeat actions from this post it will work for you, it does not. During the article, I had to do some fixes in the django-iris project, and even in DB-API driver made by InterSystems to fix some issues there as well, and I think this driver is still in development, and we will get more stable driver in future. Let's decide that this article only explains how it could be if we would have all done.

In this article, I am trying to identify the multiple areas to develop the features we can able to do using python and machine learning.

Each hospital is every moment trying to improve its quality of service and efficiency using technology and services. 

The healthcare sector is one of the very big and vast areas of service options available and python is one of the best technology for doing machine learning.

In every hospital, humans will come with some feelings, if this feeling will understand using technology is make a chance to provide better service.

Continuing to  observe the possibilities of Django, and usage with IRIS. The first we have looked how to define models and connect to tables already existing in IRIS, than we extended embedded Django Administration portal, with an ability to see what data we have in that models, with filters, editing and even pagination.

Time to go to real action, now we a going to create some REST API, on Django, based on the same data, we used before from the package posts-and-tags.

To do so, we will use Django REST Framework

Django REST framework is a powerful and flexible toolkit for building Web APIs.

Some reasons you might want to use REST framework:

• The Web browsable API is a huge usability win for your developers.
• Authentication policies including packages for OAuth1a and OAuth2.
• Serialization that supports both ORM and non-ORM data sources.
• Customizable all the way down - just use regular function-based views if you don't need the more powerful features.
• Extensive documentation, and great community support.
• Used and trusted by internationally recognised companies including Mozilla, Red Hat, Heroku, and Eventbrite.